Health, Mental Health, and the Architecture of Value-Based Care in AI

Artificial intelligence is no longer confined to research labs or technical infrastructure—it is embedded in classrooms, creative practice, healthcare systems, communication platforms, and planetary-scale infrastructures. As AI systems move from experimental tools to everyday companions, decision-makers, and mediators of social life, the question is no longer whether AI will shape our future, but how—and by whom.

At the Design Lab, we approach AI not simply as an algorithmic achievement, but as a fundamentally human-centered design challenge. Intelligent systems must be technically robust, yet responsive to lived experience; powerful at scale, yet grounded in context; innovative, yet attentive to equity and responsibility. Across seven sessions, Design@Large in Spring 2026 brings together leading voices from research, industry, education, law, health, and the arts to explore how AI is designed, deployed, governed, and experienced in real-world settings. From generative AI in education and music to embodied intelligence in XR, from disability justice and communication to sustainable computing and Indigenous data sovereignty, and from personal AI companions to value-based care in health systems, the series examines AI where it meets people, institutions, and infrastructures.

Rather than treating AI as a purely technical system, we frame it as a site of negotiation among human values, institutional incentives, cultural norms, and material conditions. Each session pairs scholars, practitioners, and industry leaders to interrogate how design decisions shape agency, creativity, trust, access, and care at scale.

Design@Large is open to the broader public and livestreamed online, while also serving as a core seminar for over 100 undergraduate and graduate students at UC San Diego. Together, we ask: What does it mean to design AI responsibly? How do we ensure that intelligent systems amplify human capability without reproducing harm? And how can design guide AI toward more just, inclusive, and sustainable futures?

AI is increasingly embedded in clinical and mental health systems, shaping how care is delivered, measured, and scaled. This session examines how AI participates in the architecture of value-based care—where outcomes, efficiency, equity, and accountability are intertwined. Bringing together computational mental health research, clinical AI deployment, women’s health innovation, and health systems expertise, the discussion explores how design decisions influence what counts as “value” in care and how AI reshapes relationships among patients, clinicians, and institutions.

Peter Westlake is the founder of MindNumbers, a San Diego-based digital health company building passive sensing and algorithmic tools for serious mental illness — tracking sleep, activity, mood, and routine to deliver personalized insights for people living with bipolar disorder and their care teams. His path to mental health technology runs through two decades of diagnostics leadership: he helped drive FDA clearance of a quantitative point-of-care platform at ProciseDx (acquired by Biosynex), and held senior roles at Prometheus Laboratories here in San Diego. That arc — from validated diagnostics to scalable digital tools — informs how he thinks about how to provide decision useful information in clinical settings: what gets measured, how it gets measured, and whether the architecture of AI-driven care serves patients. Peter serves on the Board of the International Bipolar Foundation and holds a degree in economics from the University of Cambridge.

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